A fingerprint identification technology has been widely applied to mobile terminals such as smart phones and tablet computers. M*N pixel units forming an array are arranged on a fingerprint identification sensor. According to the fingerprint identification technology, a fingerprint image of a user is acquired through each of the pixel units in the fingerprint identification sensor, and the acquired fingerprint image and a pre-stored fingerprint template are compared to match, thereby realizing functions of screen unlocking, mobile payment or the like.
A fingerprint of a user may change with age and season, so that a learning function is added to a fingerprint template in a related technology, thereby reducing a False Reject Rate (FRR) of a fingerprint identification sensor, the FRR referring to identifying the same fingerprint image into different fingerprint images. However, the learning function may add a pixel feature of a damaged pixel unit in the fingerprint identification sensor into the fingerprint template, and since the pixel feature is own feature of the fingerprint identification sensor, a False Accept Rate (FAR) of the fingerprint identification sensor is greatly increased, the FAR referring to identifying different fingerprint images into the same fingerprint image. Therefore, potential safety hazards of a mobile terminal may be incurred.